初始化项目，由ModelHub XC社区提供模型
Model: twinkle-ai/gemma-3-4B-T1-it-GGUF Source: Original Platform
This commit is contained in:
ModelHub XC
265
README.md
Normal file
265
README.md
Normal file
@@ -0,0 +1,265 @@
|
||||
---
|
||||
license: gemma
|
||||
language:
|
||||
- en
|
||||
- zh
|
||||
base_model: twinkle-ai/gemma-3-4B-T1-it
|
||||
library_name: transformers
|
||||
tags:
|
||||
- Taiwan
|
||||
- SLM
|
||||
- GGUF
|
||||
- agent
|
||||
datasets:
|
||||
- lianghsun/tw-reasoning-instruct
|
||||
- lianghsun/tw-contract-review-chat
|
||||
- minyichen/tw-instruct-R1-200k
|
||||
- minyichen/tw_mm_R1
|
||||
- minyichen/LongPaper_multitask_zh_tw_R1
|
||||
- nvidia/Nemotron-Instruction-Following-Chat-v1
|
||||
metrics:
|
||||
- accuracy
|
||||
model-index:
|
||||
- name: gemma-3-4B-T1-it
|
||||
results:
|
||||
- task:
|
||||
type: question-answering
|
||||
name: Single Choice Question
|
||||
dataset:
|
||||
name: tmmlu+
|
||||
type: ikala/tmmluplus
|
||||
config: all
|
||||
split: test
|
||||
revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
|
||||
metrics:
|
||||
- type: accuracy
|
||||
value: 47.44
|
||||
name: single choice
|
||||
- task:
|
||||
type: question-answering
|
||||
name: Single Choice Question
|
||||
dataset:
|
||||
name: mmlu
|
||||
type: cais/mmlu
|
||||
config: all
|
||||
split: test
|
||||
revision: c30699e
|
||||
metrics:
|
||||
- type: accuracy
|
||||
value: 59.13
|
||||
name: single choice
|
||||
- task:
|
||||
type: question-answering
|
||||
name: Single Choice Question
|
||||
dataset:
|
||||
name: tw-legal-benchmark-v1
|
||||
type: lianghsun/tw-legal-benchmark-v1
|
||||
config: all
|
||||
split: test
|
||||
revision: 66c3a5f
|
||||
metrics:
|
||||
- type: accuracy
|
||||
value: 44.18
|
||||
name: single choice
|
||||
pipeline_tag: text-generation
|
||||
---
|
||||
|
||||
# Gemma 3 4B T1-it GGUF Collection
|
||||
|
||||
<div align="center" style="line-height: 1;">
|
||||
<a href="https://discord.gg/Cx737yw4ed" target="_blank" style="margin: 2px;">
|
||||
<img alt="Discord" src="https://img.shields.io/badge/Discord-Twinkle%20AI-7289da?logo=discord&logoColor=white&color=7289da" style="display: inline-block; vertical-align: middle;"/>
|
||||
</a>
|
||||
<a href="https://huggingface.co/twinkle-ai" target="_blank" style="margin: 2px;">
|
||||
<img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Twinkle%20AI-ffc107?color=ffc107&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
|
||||
</a>
|
||||
<!-- Gemma 模型在 Hugging Face 上為 gated，使用者需同意 Google usage license -->
|
||||
<a href="https://huggingface.co/google/gemma-3-4b-pt" style="margin: 2px;">
|
||||
<img alt="License" src="https://img.shields.io/badge/License-gemma-f5de53?&color=0081fb" style="display: inline-block; vertical-align: middle;"/>
|
||||
</a>
|
||||
</div>
|
||||
|
||||
GGUF quantized models converted from [twinkle-ai/gemma-3-4B-T1-it](https://huggingface.co/twinkle-ai/gemma-3-4B-T1-it) for use with llama.cpp.
|
||||
|
||||
|
||||
|
||||
## About
|
||||
|
||||
Gemma 3 4B T1-it is a small language model fine-tuned on Taiwan-focused datasets, supporting both English and Traditional Chinese. This repository provides multiple quantization formats optimized for different use cases.
|
||||
|
||||
## Available Models
|
||||
|
||||
| Model | Size | Use Case |
|
||||
| ----- | ---- | -------- |
|
||||
| `twinkle-ai-gemma-3-4B-T1-it-BF16.gguf` | Largest | Best quality, highest precision |
|
||||
| `twinkle-ai-gemma-3-4B-T1-it-F16.gguf` | Large | High quality, good precision |
|
||||
| `twinkle-ai-gemma-3-4B-T1-it-Q8_0.gguf` | Medium | Balanced quality and speed |
|
||||
| `twinkle-ai-gemma-3-4b-t1-it-q4_k_m.gguf` | Smallest | Fastest inference, lower memory |
|
||||
|
||||
## Quick Start
|
||||
|
||||
### Option 1: Using Hugging Face Hub (Recommended)
|
||||
|
||||
Install llama.cpp via Homebrew:
|
||||
|
||||
```bash
|
||||
brew install llama.cpp
|
||||
```
|
||||
|
||||
Run inference directly from Hugging Face:
|
||||
|
||||
```bash
|
||||
llama-cli --hf-repo thliang01/gemma-3-4B-T1-it-Q8_0-GGUF \
|
||||
--hf-file gemma-3-4b-t1-it-q8_0.gguf \
|
||||
-p "Your prompt here"
|
||||
```
|
||||
|
||||
Start as a server:
|
||||
|
||||
```bash
|
||||
llama-server --hf-repo thliang01/gemma-3-4B-T1-it-Q8_0-GGUF \
|
||||
--hf-file gemma-3-4b-t1-it-q8_0.gguf \
|
||||
-c 2048
|
||||
```
|
||||
|
||||
### Option 2: Build from Source
|
||||
|
||||
#### Step 1: Clone llama.cpp repository
|
||||
|
||||
```bash
|
||||
git clone https://github.com/ggerganov/llama.cpp
|
||||
cd llama.cpp
|
||||
```
|
||||
|
||||
#### Step 2: Build llama.cpp
|
||||
|
||||
Basic build (CPU only):
|
||||
|
||||
```bash
|
||||
LLAMA_CURL=1 make
|
||||
```
|
||||
|
||||
**Hardware-specific build options:**
|
||||
|
||||
- **NVIDIA GPU (Linux)**:
|
||||
```bash
|
||||
LLAMA_CUDA=1 LLAMA_CURL=1 make
|
||||
```
|
||||
|
||||
- **Apple Silicon (Mac)**:
|
||||
```bash
|
||||
LLAMA_METAL=1 LLAMA_CURL=1 make
|
||||
```
|
||||
|
||||
- **AMD GPU (ROCm)**:
|
||||
```bash
|
||||
LLAMA_HIPBLAS=1 LLAMA_CURL=1 make
|
||||
```
|
||||
|
||||
#### Step 3: Run inference
|
||||
|
||||
```bash
|
||||
./llama-cli --hf-repo thliang01/gemma-3-4B-T1-it-Q8_0-GGUF \
|
||||
--hf-file gemma-3-4b-t1-it-q8_0.gguf \
|
||||
-p "Your prompt here"
|
||||
```
|
||||
|
||||
#### Step 4: Start server (optional)
|
||||
|
||||
```bash
|
||||
./llama-server --hf-repo thliang01/gemma-3-4B-T1-it-Q8_0-GGUF \
|
||||
--hf-file gemma-3-4b-t1-it-q8_0.gguf \
|
||||
-c 2048
|
||||
```
|
||||
|
||||
## Advanced Usage
|
||||
|
||||
### Choosing the Right Model
|
||||
|
||||
Select a model based on your needs:
|
||||
|
||||
- **Best Quality**: Use `BF16` or `F16` versions (requires more memory)
|
||||
- **Balanced**: Use `Q8_0` version (recommended for most users)
|
||||
- **Resource Constrained**: Use `q4_k_m` version (suitable for devices with limited memory)
|
||||
|
||||
### Common Parameters
|
||||
|
||||
- `-p "prompt"`: Your input text for the model to respond to
|
||||
- `-c 2048`: Context length (maximum number of tokens that can be processed)
|
||||
- `--hf-repo`: Hugging Face repository name
|
||||
- `--hf-file`: Model file name to use
|
||||
|
||||
### Adjusting Generation Parameters
|
||||
|
||||
```bash
|
||||
llama-cli --hf-repo thliang01/gemma-3-4B-T1-it-Q8_0-GGUF \
|
||||
--hf-file gemma-3-4b-t1-it-q8_0.gguf \
|
||||
-p "Your prompt here" \
|
||||
--temp 0.7 \
|
||||
--top-p 0.9 \
|
||||
--repeat-penalty 1.1
|
||||
```
|
||||
|
||||
Parameter explanations:
|
||||
|
||||
- `--temp`: Temperature (0.0-2.0), higher values produce more random output
|
||||
- `--top-p`: Nucleus sampling parameter (0.0-1.0)
|
||||
- `--repeat-penalty`: Repetition penalty to avoid repetitive content
|
||||
|
||||
## Model Information
|
||||
|
||||
- **Base Model**: twinkle-ai/gemma-3-4B-T1-it
|
||||
- **Languages**: English, Traditional Chinese
|
||||
- **License**: Gemma
|
||||
- **Format**: GGUF (converted via [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo))
|
||||
|
||||
### Training Data
|
||||
|
||||
- Taiwan reasoning and instruction datasets
|
||||
- Contract review and legal documents
|
||||
- Multimodal and long-form content
|
||||
- Instruction-following examples
|
||||
|
||||
### Benchmarks
|
||||
|
||||
- **TMMLU+**: 47.44% accuracy
|
||||
- **MMLU**: 59.13% accuracy
|
||||
- **TW Legal Benchmark**: 44.18% accuracy
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Common Issues
|
||||
|
||||
**Q: Getting out of memory errors?**
|
||||
|
||||
A: Try using a smaller quantized version like `q4_k_m`, or reduce the context length parameter `-c`.
|
||||
|
||||
**Q: How can I speed up inference?**
|
||||
|
||||
A:
|
||||
|
||||
1. Use GPU acceleration (add hardware-specific flags during compilation)
|
||||
2. Choose a smaller quantized model (like `q4_k_m`)
|
||||
3. Reduce context length
|
||||
|
||||
**Q: What prompt format does the model support?**
|
||||
|
||||
A: This is an instruction-tuned model. Use a clear instruction format, for example:
|
||||
|
||||
```text
|
||||
Please analyze the main clauses of the following contract: [contract content]
|
||||
```
|
||||
|
||||
## Links
|
||||
|
||||
- [Original Model](https://huggingface.co/twinkle-ai/gemma-3-4B-T1-it)
|
||||
- [llama.cpp Documentation](https://github.com/ggerganov/llama.cpp)
|
||||
- [GGUF Format Documentation](https://github.com/ggerganov/ggml/blob/master/docs/gguf.md)
|
||||
|
||||
## Contributing
|
||||
|
||||
If you have any questions or suggestions, please feel free to open a discussion in the Hugging Face repository.
|
||||
|
||||
---
|
||||
|
||||
**Note**: On first run, llama.cpp will automatically download the model file from Hugging Face. Please ensure you have a stable internet connection.
|
||||
Reference in New Issue
Block a user